Terminological modelling represents the definitions and essential properties of concepts. The terminological definition of a concept provides sufficient information to define, or recognize, that concept. Contrast this with, for example, modelling facts or assertions about concepts, which we may know to be true in the world, either about particular concepts, or the interaction between them, but which do not add to the definition of those concepts. For example, wine might be defined as a drink made of distilled grape juice. Other information not part of the definition might include that wines are either red or white.
Terminology may be seen as the definitional backbone of the concept structure that we wish to describe. It may well be the case that one of the important uses of such a structure is to handle non-definitional assertions about the real world. The features GRAIL provides to handle assertions will be illustrated in the examples.
Terminological models are also called ontologies by many authors, although other authors use the word ontologies to indicate a rather broader kind of knowledge base than that which we consider terminological.
Finally, it is not always clear whether what you wish to say falls into the category of terminological knowledge, or not. Dont worry, but come back to this point later, after you’ve been through the tutorial. If in doubt, raise the issue personally or by email.
Angus Roberts is an expert in healthcare IT and HIPAA compliance. He has a strong expertise in AI and Cloud technologies and has been working with these technologies for the past decade. Angus is also a frequent speaker at conferences in the US and Europe on topics related to cloud, AI, healthcare IT, HIPAA compliance, cybersecurity, data privacy and more.